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The IDefix project aims to innovate polymer design through data-driven methods to improve adhesive properties. By utilizing advanced statistical analysis and machine learning, it seeks to create polymers with enhanced functionalities for applications such as coatings and drug delivery systems.
Generating novel polymer functions based on rational design criteria, derived from deep statistical analysis of massive experimental data sets, would fundamentally impact materials development and represent the next evolutionary step in macromolecular engineering.The IDefix project establishes a generic information-based design strategy to define polymer–surface interactions that represent the key property in various applications.
The project focuses on advancing adhesives, to facilitate materia…
HUMBOLDT-UNIVERSITAET ZU BERLIN
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